Enterprise Industries

Demand = Y = demand for a large size bottle of Fresh (in 100,000)

Price = the price of Fresh as offered by Enterprise Industries

AIP = the average industry price

Adv = Ent. Industries Advertising Expenditure (in $100,000) to Promote Fresh in the sales period.

Diff = AIP - Price = the "price difference" in the sales period

Enterprise Industries produces Fresh, a brand of liquid detergent. In order to more effectively manage its inventory, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 33 sales periods. Each sales period is defined as one month. The variables are as follows:

1. Use regression to perform trend analysis on the de-seasonalized demand values. Is trend analysis suitable for this data? Find MAD and explain the Excel Regression output (trend equation, r, r-squared, goodness of model).
2. Find the seasonally adjusted trend forecasts for March through May 2022.
3. Perform simple linear regression analysis with ADV as the independent variable. Write the complete equation, find MAD and explain the Excel Regression output. Make sure to use the de-seasonalized demand data for this model and all future models.
4. Repeat part (i) with Diff as the independent variable.
5. Construct multiple linear regression model with Period, AIP, Diff, and Adv as independent variables. Formulate the equation, find MAD, and explain the output. Rank variables based on their degree of contribution to the model. Observe significant F, R-squared, and p-values and explain.
6. Perform multiple linear regression analysis with Period, Diff, and Adv as independent variables. Formulate the equation and find MAD. Which variable is the most significant predictor of demand? Rank the independent variables based on their degree of contribution to the model. Observe significant F, R-squared, and p-values and explain.

7. Period Price AIP Adv

   March 2022 $7.28 $7.41 $10.29

   April 2022 $7.17 $7.65 $11.71

   May 2022 $7.46 $7.82 $10.12

   Use the model in part (l) and make forecasts for the following months. Make sure to seasonalize final forecasts.
8. Provide analytical conclusion for the case based on above analysis.